We present in this article two components: these components can in fact serve various goals
independently, though we consider them here as an ensemble. The first component is a technique for
the rapid and reliable evaluation prediction of linear functional outputs of elliptic (and
parabolic) partial differential equations with affine parameter dependence.
The essential features are (i) (provably) rapidly convergent global
reduced–basis approximations — Galerkin projection onto a space
WN spanned by solutions of the governing partial differential
equation at N selected points in parameter space; (ii) a
posteriori error estimation — relaxations of the error–residual
equation that provide inexpensive yet sharp and rigorous bounds for
the error in the outputs of interest; and (iii) off–line/on–line
computational procedures — methods which decouple the generation
and projection stages of the approximation process. This component is ideally suited — considering
the operation count of the online stage — for the repeated and rapid evaluation required in the
context of parameter estimation, design, optimization, and
real–time control. The second component is a framework for distributed simulations. This framework
comprises a library providing the necessary abstractions/concepts for distributed simulations and a
small set of tools — namely SimTeXand SimLaB— allowing an easy manipulation of those
simulations. While the library is the backbone of the framework and is therefore general, the
various interfaces answer specific needs. We shall describe both components and present how they
interact.

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